In this short post, we are going to solve a few problems involving Uniform Distribution. Uniform Distribution is yet another favorite of many interviewers, and nailing any problems involving Uniform Distribution really makes your candidacy stand out
We are continuing our series on cracking Data Science interviews. So far, we have worked out a [few_](https://medium.com/swlh/linear-regression-and-maximum-likelihood-1dcb9435c71e)[_examples_](https://medium.com/swlh/maximum-likelihood-and-data-science-interviews-c31b1d5b4e4a) on Maximum Likelihood Estimator (MLE). In this short post, we are going to solve a few problems involving Uniform Distribution. Uniform Distribution is yet another favorite of many interviewers, and nailing any problems involving Uniform _Distribution really makes your candidacy stand out 🙂
A uniform distribution over the bounds a and b has the following probability density function:
Probability Density Function of Uniform Distribution
Here is the curve for the pdf from Wikipedia:
Recall that the_ Cumulative Distribution Function (CDF) _of a uniform distribution is given by
Cumulative Distribution Function of Uniform Distribution
We are going to use the CDF (instead of PDF) a lot in this post! Make sure you understand the formula above.
Finally, we are mainly going to deal with a Uniform Distribution over the interval [0, 1]. We are also going to ignore the range outside the interval [0, 1]. The formulae for PDF and CDF simplify to the following forms for this simple interval:
12 Most Common Probability and Statistics questions for Data Science Interview. Here are the most common data science interview questions on Probability and Statistics.
Top Android Interview Questions & Answers from Beginner to Advanced level. Get ready to crack your next android interview with these android interview questions
Find out here. Although data science job descriptions require a range of various skillsets, there are concrete prerequisites that can help you to become a successful data scientist. Some of those skills include, but are not limited to: communication, statistics, organization, and lastly, programming. Programming can be quite vague, for example, some companies in an interview could ask for a data scientist to code in Python a common pandas’ functions, while other companies can require a complete take on software engineering with classes.
Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.